In a turbo interference cancellation receiver, interference such as inter-symbol-interference (ISI), code-division multiplexing (CDM) interference, and spatial-multiplexing interference due to single-user (SU) or multi-user (MU) MIMO can be cancelled based on soft estimates of the interfering symbols. The soft symbol estimates are formed using the decoder outputs, which describe the likelihood ratios of the bits that are used to determine these interfering symbols. Each likelihood ratio can be converted to bit probability (i.e., probability of bit having value 0 or 1). After cancellation, the received signal is re-equalized using new combining weights, which reflect a new impairment covariance matrix due to interference cancellation. The equalized symbols are demodulated and converted to bit soft values, which are used by the various decoders, one for each user, codeword or MIMO stream, to produce updated bit likelihood ratios. This iterative process of cancellation, equalization, demodulation, and decoding is referred to as turbo interference cancellation (turbo-IC).
One key aspect of turbo-IC implementation is adapting the equalizer formulation to the residual impairment characteristics. In some radio base stations (RBSs), despread-level equalization such as G-Rake or G-Rake+ is used. The received signal is descrambled and despread for a symbol of interest and for a number of finger delays. The multiple despread values are combined according to a set of combining weights, which is dependent on the impairment covariance matrix. In the G-Rake approach, an estimate of the code-averaged impairment covariance matrix is obtained by parametrically formulating a self-interference covariance matrix using the estimated own-signal propagation characteristics while interference from other interfering signals and thermal noise is modeled as additive white Gaussian noise (AWGN). In the G-Rake+ approach, an estimate of the code-averaged impairment covariance matrix can be obtained by observing the despread values on one or more unoccupied codes. Previous studies have confirmed that such a practical approach captures the overall interference characteristics more accurately and results in good performance relative to a G-Rake+ receiver that has perfect knowledge about the impairment covariance matrix. Another commonly used receiver in a CDMA system is Rake receiver which models overall interference as AWGN.
Finger delays (or finger placement) and combining weights are two important design parameters for a G-Rake+ equalizer. In a practical iterative multi-stage interference-cancellation based multiuser detector (MUD), or turbo-IC receiver, interference characteristics can change as a portion of the interference is cancelled. It would thus be desirable to update covariance estimates and combining weights.